Growing scientific evidence suggests that risks due to failure of critical infrastructures (CIs) will increase worldwide, as the frequency and intensity of extreme weather events (EWEs) induced by climate change increases. Such risks are difficult to estimate due to the increasing complexity and interconnectedness of CIs and because information sharing regarding the vulnerabilities of the different CIs is limited. This paper proposes a methodology for risk analysis of systems of interdependent CIs to EWEs. The methodology is developed and carried out for the Port of Rotterdam area in the Netherlands, which is used as a case study. The case study includes multiple CIs that belong to different sectors and can be affected at the same time by an initiating EWE. The proposed methodology supports the assessment of common cause failures that cascade across CIs and sectors. It is based on a simple, user-friendly approach that can be used by CIs owners and operators. The implementation of the methodology has shown that the severity of cascading effects is strongly influenced by the recovery time of the different CIs due to the initiating EWE and that cascading effects that result from a disruption in a single CI develop differently from cascading effects that result from common cause failures. For most CIs, vulnerabilities from EWEs on the CI level will be higher than the cascading risks of common cause failures on the system of CIs; moreover, cascading risks for a CI will increase after its recovery from the event.

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Abstract. The resilience of critical infrastructures (CI) to Extreme Weather Events (EWE) is one of the most salient and demanding challenges facing society. Growing scientific evidence suggests that more frequent and severe weather extremes such as heat waves, hurricanes and droughts and their effects such as flooding are having an ever increasing impact, with the range and effects on society exacerbated when CI is disrupted or destroyed. Disruptions of CI systems frequently cause major social and economic losses, both directly and through failures in one system leading to disruptions in another (cascading effects). The ability to ensure continuity in services provided by CI directly relates to the resilience of communities to withstand and recover from disasters. The approach adopted by the INTACT-project recognizes that a European-wide coordinated and cooperative effort is required because of cross border CI-activities and impacts as well as an integrated EU-policy.The INTACT-case studies and their expected outcomes are designed to bring added value for the concerned stakeholders locally and demonstrate the validity and applicability of the INTACT approach at the broader (European) scale. To achieve this, the selected case studies are geographically spread across Europe encompassing different climate, landscape and environmental zones, as to provide coverage of a representative range of CI types and also including different levels of governance.One of the case studies is located in the Netherlands and deals with the port of Rotterdam. The situation in Rotterdam is representative for many other main ports in Europe. These ports are all situated in a delta area, near the sea and rivers or canals. Also, these ports are close to urban areas and industrial complexes. Finally, these ports have a multimodal transport infrastructure to and from its hinterland, which is also vulnerable for extreme weather events. The case study is not only significant for the development of methods and tools, but also of direct interest for the region itself. The combination of the National Water safety policy and the best practices from the INTACT cases offer challenges to create better adaptation options and coping capacity to these relatively unforeseen and unexpected impacts based on climate cKDQJH VFHQDULR ¶V DQG VRFLR-economic megatrends.

Tolerance analysis consists of analyzing the impact of variations on the mechanism behavior due to the manufacturing process. The goal is to predict its quality level at the design stage. The technique involves computing probabilities of failure of the mechanism in a mass production process. The various analysis methods have to consider the component's variations as random variables and the worst configuration of gaps for over-constrained systems. This consideration varies in function by the type of mechanism behavior and is realized by an optimization scheme combined with a Monte Carlo simulation. To simplify the optimization step, it is necessary to linearize the mechanism behavior into several parts. This study aims at analyzing the impact of the linearization strategy on the probability of failure estimation; a highly over-constrained mechanism with two pins and five cotters is used as an illustration for this study. The purpose is to strike a balance among model error caused by the linearization, computing time, and result accuracy. In addition, an iterative procedure is proposed for the assembly requirement to provide accurate results without using the entire Monte Carlo simulation.